The UNC CERTs proposes to develop, test, validate, and disseminate a standardized, user-friendly software tool for obtaining doubly robust estimate of treatment effects in SAS(r). In one set of extensive simulations, doubly robust methods have been shown to provide additional insurance against bias due to confounding, maintaining a bias <1% and correct coverage of 95% confidence intervals despite omission of a key confounder and a moderate to strong prognostic factor from one of its two component models. The proposed SAS tool will incorporate a point-and-click windows interface and will make it easier for epidemiologists and biostatisticians to use this recently developed analytic method to reduce effects of confounding and selection bias in analyses of observational studies of the safety and effectiveness of drugs. Doubly robust methods are not currently available in standard software packages, necessitating the use of custom programming. The availability of an easy-to-use tool clearly will further investigators' efforts to close gaps in priority area research on comparative effectiveness, as explicitly mandated in Section 1013 of the Medicare Prescription Drug, Improvement, and Modernization Act (MMA, PL 1008-173). Our aims focus on the class of estimators that includes doubly robust methods and other inverse probability of treatment weighted estimates (IPTW). We will develop, document, test and validate SAS macros with a graphical user interface for doubly-robust and IPTW methods, focusing on the case of a point exposure or treatment. We will conduct usability testing with participants in a causal modeling course at UNC. Responding to the RFA's strong encouragement of "coordinated, complementary, and collaborative applications" (p. 7), we will collaborate explicitly with the Duke CERTs investigators to evaluate the usability of the SAS software tool in their analysis of the effectiveness of beta-blockers for which clinical trial evidence of effectiveness exists (carvedilol, metoprolol succinate, and bisoprolol fumarate) with that of older, off-patent beta-blockers in reducing mortality among patients with congestive heart failure. Finally, we will disseminate this tool through publications in technical and scientific journals, a website and through AHRQ, and the other CERTs, to as broad an audience as possible. Relevance: The Medicare Prescription Drug Benefit, Improvement, and Modernization Act calls for new scientific information to close gaps in our knowledge about the comparative effectiveness of drugs. Freely available, usable analytical software incorporating recent advances in statistical theory, as we propose to develop here, can help create that new scientific information. [unreadable] [unreadable] [unreadable]